Modeling and Implementation of an Adaptive Wireless Sensor Network for Low Power IoT Applications

Wireless Sensor Networks (WSNs) consist of low cost and energy small electronic devices such as sensors, actuators, routers and gateways. A WSN can sense various type of data, such as temperature, humidity, pH.. etc, with the sensors scattered on an agricultural region and collect the data at a cloud database via multi-hop data transmission routes. The number of periods that a WSN operates is the network lifetime which strongly depends on the limited battery energy of the devices. Hence, in order to prolong the lifetime, we propose a centralized mathematical model which deploys minimum number of devices within limited budget, efficiently utilizes the device battery by planning their active/sleep schedules and determining the minimum energy consuming data flow paths towards the cloud. We also realized the proposed model on hardware level using low power embedded system architectures.